Skill assessment of ocean data for emergency and SAR operation (IBISAR)
Search and Rescue operators, marine pollution and maritime traffic controllers need the most reliable forecasts to accurately predict trajectories of drifting targets to determine an optimal search region. As the reliability of the prediction depends on the accuracy of current and wind provided by forecast models, RPS will update the database of ocean current forecast models, drifter trajectories and HF Radar derived surface currents in the IBI region. In order to facilitate better selection of forecast models, data viewer will be developed with the options of display customization and inter-comparison of data. Finally, a skill assessment service will be delivered to provide an easily interpretable metric of current forecast accuracy.
This project is done in partnership with the Balearic Islands Coastal Observing and Forecasting System (SOCIB – www.socib.es) and AZTI tecnalia (www.azti.es/en/), with the collaboration of the Spanish Maritime Safety Agency (SASEMAR – www.salvamentomaritimo.es) and the Spanish Port System (PUERTOS - www.puertos.es/en-us).
Key Details
Project Name
Skill assessment service for real-time ocean data product ranking in the IBI area for emergency and SAR operators (IBISAR)
Sector
- Transport - Ports and Maritime
- Defense and government services - Security and Safety
Funder
- Mercator Ocean International
Location
- Iberian-Biscay-Irish (IBI) regional seas
Services Provided
Updated database of ocean current forecast models, drifter trajectories and High-Frequency (HF) Radar derived surface currents in the IBI regional seas.
Data viewer with display customization and inter-comparison of data.
Skill assessment service providing an easily interpretable metric of current forecast accuracy.
Challenge
The accuracy of wind and current data makes a huge impact on the reliability of trajectory prediction in marine environment. The challenge here is to provide the client with updated current datasets and developing tools to select best dataset to be used in trajectory prediction model.
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